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Design of a rapid diagnostic model for bladder compliance based on real-time intravesical pressure monitoring system
Zicong Ge1, Liangfeng Tang2, Yunsong Peng1
1School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230022, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
Insights
Diagnosing pediatric bladder dysfunction is improved by a new method measuring intravesical pressure during voiding cystourethrogram (VCUG) exams. This approach aids in assessing bladder compliance, potentially reducing the need for separate urodynamic studies (UDS).
Area of Science:
- Biomedical Engineering
- Medical Diagnostics
- Pediatric Urology
Background:
- Pediatric bladder dysfunction diagnosis relies on abnormal bladder shape and compliance.
- Current methods require separate voiding cystourethrogram (VCUG) and urodynamic studies (UDS) examinations, increasing patient burden.
- There is a need for a less invasive and more efficient diagnostic approach.
Purpose of the Study:
- To develop a novel method for assessing bladder compliance during VCUG examinations.
- To reduce the time and discomfort associated with diagnosing bladder dysfunction in children.
- To integrate intravesical pressure measurement into the existing VCUG procedure.
Main Methods:
- A single-tube device was developed to measure, display, store, and transmit real-time intravesical pressure.
- Clinical trials were conducted on 52 pediatric patients.
- Data preprocessing, feature extraction (including time-domain, wavelet, and frequency-domain features), feature selection using LASSO, and machine learning classification (SVM, Random Forest, XGBoost, etc.) were performed.
Main Results:
- 73 features were extracted, with 15 key features selected.
- The Support Vector Machine (SVM) algorithm achieved the highest Area Under the Curve (AUC) of 0.873.
- The classification accuracy reached 84% for predicting bladder compliance level.
Conclusions:
- A system was designed to rapidly obtain intravesical pressure during VCUG.
- The developed classification model demonstrates competitive performance in judging bladder compliance.
- This method offers a potential for rapid auxiliary diagnosis of bladder diseases, aiding clinical decisions before UDS.
Objective:
The diagnosis of bladder dysfunction for children depends on the confirmation of abnormal bladder shape and bladder compliance. The existing gold standard needs to conduct voiding cystourethrogram (VCUG) examination and urodynamic studies (UDS) examination on patients separately. To reduce the time and injury of children's inspection, we propose a novel method to judge the bladder compliance by measuring the intravesical pressure during the VCUG examination without extra UDS.
Methods:
Our method consisted of four steps. We firstly developed a single-tube device that can measure, display, store, and transmit real-time pressure data. Secondly, we conducted clinical trials with the equipment on a cohort of 52 patients (including 32 negative and 20 positive cases). Thirdly, we preprocessed the data to eliminate noise and extracted features, then we used the least absolute shrinkage and selection operator (LASSO) to screen out important features. Finally, several machine learning methods were applied to classify and predict the bladder compliance level, including support vector machine (SVM), Random Forest, XGBoost, perceptron, logistic regression, and Naive Bayes, and the classification performance was evaluated.
Results:
73 features were extracted, including first-order and second-order time-domain features, wavelet features, and frequency domain features. 15 key features were selected and the model showed promising classification performance. The highest AUC value was 0.873 by the SVM algorithm, and the corresponding accuracy was 84%.
Conclusion:
We designed a system to quickly obtain the intravesical pressure during the VCUG test, and our classification model is competitive in judging patients' bladder compliance.
Significance:
This could facilitate rapid auxiliary diagnosis of bladder disease based on real-time data. The promising result of classification is expected to provide doctors with a reliable basis in the auxiliary diagnosis of some bladder diseases prior to UDS.
Related Concept Videos
01:19Urodynamic Studies: Uroflowmetry
01:24Imaging Studies II: Ultrasonography
01:22Imaging Studies VI: Voiding Cystourethrography and Cystography